General Anesthesia Versus Conscious Sedation with Locoregional Anesthesia in S-ICD Implantation: A Monocentric Retrospective Analysis
Bibliographic record
Abstract
Abstract Background The subcutaneous implantable cardioverter-defibrillator (S-ICD) is a safe and effective alternative to the transvenous ICD (TV-ICD). Historically, S-ICD implantations have been performed under general anesthesia (GA). This study examines whether conscious sedation with locoregional anesthesia (CS-LA) is a safe and effective alternative to GA in S-ICD implantation. Methods 138 S-ICD implantations (90 CS-LA) at our institution between 2013-2020 were studied. Analgesic efficacy in the 24 post-operative hours was evaluated by Numerical Pain Rating Scale (NPRS) score and by total analgesic medication received. Safety was evaluated by comparing the incidence of significant adverse events (AE): hypotension <80 mmHg or requiring vasopressors, bradycardia <40 bpm, or desaturation <90% or requiring non-invasive ventilation maneuvers. Results Post-procedural pain at 15 minutes and 24 hours was significantly less in CS-LA (-0.90 (p=0.04) and -1.21 (p=0.004), respectively). Post-procedural opioid consumption was 10.64mg of per osmorphine equivalents (p=0.046) lower in CS-LA. No significant difference in the likelihood ≥1 adverse event was noted (CS-LA OR 1.95 (95% CI [0.86, 4.40], p=0.11)). Conclusion S-ICD implantation under CS-LA was at least equivalent to GA in terms of analgesic efficacy and demonstrated a comparable safety profile. CS-LA represents a possible alternative to GA during S-ICD implantation in sites without readily available anesthesiologists.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".